4 papers · 1 filter
Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation
Nader Aldoj, Federico Biavati, Marc Dewey +3
Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using tr…
Unsupervised Adaptive Neural Network Regularization for Accelerated Radial Cine MRI
Andreas Kofler, Marc Dewey, Tobias Schaeffter +2
In this work, we propose an iterative reconstruction scheme (ALONE - Adaptive Learning Of NEtworks) for 2D radial cine MRI based on ground truth-free unsupervised learning of shall…
Neural Networks-based Regularization for Large-Scale Medical Image Reconstruction
Andreas Kofler, Markus Haltmeier, Tobias Schaeffter +4
In this paper we present a generalized Deep Learning-based approach for solving ill-posed large-scale inverse problems occuring in medical image reconstruction. Recently, Deep Lear…
Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited Data
Andreas Kofler, Marc Dewey, Tobias Schaeffter +2
In this work we reduce undersampling artefacts in two-dimensional () golden-angle radial cine cardiac MRI by applying a modified version of the U-net. We train the network on $…